UDEMY 2021 - Artificial Intelligence I: Basics and Games in Java

David K Mar 28, 2020

artificial_intelligence_i_basics_and_games_in_java.jpg | A&H Business Technology

A guide how to create smart applications, AI, genetic algorithms, pruning, heuristics and metaheuristics

You can find "Download Link" as a button at the end of this article.

What you’ll learn

Get a good grasp of artificial intelligence

Understand how AI algorithms work

Able to create AI algorithms on your own from scratch

Understand meta-heuristics

Requirements

Basic Java (SE)

Some basic algorithms ( maximum/minimum finding )

Basic math ( functions )

Description

This course is about the fundamental concepts of artificial intelligence. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detecting cancer for example. We may construct algorithms that can have a very good guess about stock price movement in the market.

Section 1:

path findinf algorithms

graph traversal (BFS and DFS)

enhanced search algorihtms

A* search algorithm

Section 2:

basic optimization algorithms

brute-force search

stochastic search and hill climbing algorithm

Section 3:

heuristics and meta-heuristics

tabu search

simulated annealing

genetic algorithms

particle swarm optimization

Section 4:

minimax algorithm

game trees

applications of game trees in chess

tic tac toe game and its implementation

In the first chapter we are going to talk about the basic graph algorithms. Several advanced algorithms can be solved with the help of graphs, so as far as I am concerned these algorithms are the first steps.

Second chapter is about local search: finding minimum and maximum or global optimum in the main. These searches are used frequently when we use regression for example and want to find the parameters for the fit. We will consider basic concepts as well as the more advanced algorithms: heuristics and meta-heuristics.

The last topic will be about minimax algorithm and how to use this technique in games such as chess or tic-tac-toe, how to build and construct a game tree, how to analyze these kinds of tree like structures and so on. We will implement the tic-tac-toe game together in the end.

Thanks for joining the course, let’s get started!